Internet service discovery is an emerging topic to study the deployment of protocols. Towards this end, our community periodically scans the entire advertised IPv4 address space. In this paper, we question this principle. Being good Internet citizens means that we should limit scan traffic to what is necessary. We conducted a study of scan data, which shows that several prefixes do not accommodate any host of interest and the network topology is fairly stable. We argue that this allows us to collect representative data by scanning less. In our paper, we explore the idea to scan all prefixes once and then identify prefixes of interest for future scanning.Based on our analysis of the censys.io data set (4.1 TB data encompassing 28 full IPv4 scans within 6 months) we found that we can reduce scan traffic between 25-90% and miss only 1-10% of the hosts, depending on desired trade-offs and protocols.
In our paper we analyze the attack surface of German hospitals and healthcare providers in 2020 during the COVID-19 Pandemic. The analysis looked at the publicly visible attack surface utilizing a Distributed Cyber Recon System, utilizing distributed Internet scanning, Big Data methods and scan data of 1,483 GB from more than 89 different global Internet scans. From the 1,555 identified German clinical entities, security posture analysis was conducted by looking at more than 13,000 service banners for version identification and subsequent CVE-based vulnerability identification. Primary analysis shows that 32 percent of the analyzed services were determined as vulnerable to various degrees and 36 percent of all hospitals showed numerous vulnerabilities. Further resulting vulnerability statistics were mapped against size of organization and hospital bed count.
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